Our PhD and MS level biostatisticians are highly trained in a range of statistical and analytic methods, including:
- Longitudinal data analysis
- ANOVA, regression, logistic regression
- Bayesian data analyses
- Sample size and power estimation
- Statistical genomics
- Survival analyses
- Principal component and factor analysis
- Path modeling
- Structural equation modeling
- Cluster analysis
- Complex survey data analysis
- Statistical simulations and graphics
- Profile analysis
- Gene expression data analysis
- Mixed effects models
- Generalized Estimating Equations (GEE)
- Propensity Score Matching (PSM)
- Evaluation of medical tests for classification and prediction
- Estimation of median lethal doses (LD50)/quantal dose-response curves
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Biostatisticians & Epidemiologists
Xinhua Yu, MD, PhD Assistant Professor of Epidemiology, University of Memphis Xinhua Yu, MD, PhD, MStat, is an Assistant Professor of Epidemiology at the School of Public Health, University of Memphis. He earned a medical degree in preventive medicine from Shanghai Medical University (now College of Medicine at Fudan University) in Shanghai, China, and a PhD in epidemiology and MStat in statistics from the University of Minnesota at Twin Cities campus. Dr. Yu has extensive experience in cardiovascular disease epidemiology, obesity, and physical activity. His recent research interests are clinical epidemiology especially cancer epidemiology.
Zoran Bursac, PhD Professor of Biostatistics, Preventive Medicine Zoran Bursac, PhD, MPH, is a Professor in the Division of Biostatistics and Associate Director and Senior Statistical Scientist in the Center for Population Sciences, in the Department of Preventive Medicine at the University of Tennessee Health Science Center. His background is in computer science and mathematics, and graduate work in biostatistics from The University of Oklahoma Health Science Center. His research areas of interest include logistic regression, repeated measures, missing data, categorical data analysis, variable selection algorithms, cluster randomized studies and nesting, in the chronic disease fields of obesity, weight loss, alcohol, tobacco and cancer prevention.